Ingenious E-Brain Solutions

Artificial intelligence (AI) transforms according to the interaction, consumer information, and goods and services across industries. In the healthcare industry, AI is already changing patients’ experiences, how clinicians practice medicine, and how the pharmaceutical industry operates. Although, Artificial Intelligence plays an important role in different aspects of medical diagnosis like medical decision making, management, automation, admin, and workflows. It can be used to diagnose cancer, triage critical findings in medical imaging, acute flag abnormalities, help radiologists prioritize life-threatening cases, diagnose cardiac arrhythmias, predict stroke outcomes, and help manage chronic diseases. Since the, 1970s diagnostics and treatment have been the prime focus of AI, as MYCIN was developed at Stanford for diagnosing blood-borne bacterial infections. MYCIN and other early rule-based systems showed promise for diagnosing and treating disease accurately but were not adopted ...

The 3D printing technology has matured as a viable solution for easily manufacturing intricate designs, even utilizing many materials. But it boosts the ultimate question of “What else can be done with it?”, this question has led many industry leaders and researchers to take the technology to a whole new level. The answer might lie in a new aspect of the technology – 4D printing. The Technology The term 4D printing was coined by MIT’s Self-Assembly Lab. It is an advancement of 3D printing, in which the objects created by 3D printing can change their shape, size, color, function, etc., based on the requirements. “….you first have to have the 3D manufacturing capability, and then you add smart materials….” -           Howon Lee, Associate professor, Mechanical and Space Engineering, Rutgers University This quote signifies that you can switch to 4D printing with the help of smart materials, and the rest of the process remains quite s...

The Chimeric antigen receptor CAR-T cell therapy has revolutionized the immunotherapy field with its high success rate against hematological diseases. Investigations in the early 1980s conceived the idea about tumor-infiltrating lymphocytes; however, reproducibility in invitro hampered further developments. It was not until 1993 Immunologist Dr. Zelig Eshhar created the first generation of chimeric T cells at the Weizmann Institute, Israel. The first-generation was successful during experiments, although not clinically effective. Since then, over three decades, a significant chunk of scientific intellect and considerable Research in cancer immunology has optimized this technology further. Stepping forward to 2021, we got 5 FDA-approved drugs, Diverse manufacturing platforms, an estimated billion-dollar market, and more than 250 players have invested their portfolios into generating/marketing/manufacturing CAR-T-based therapeutics. Furthermore, now CAR T-based therapies have expanded ...

Genetic testing identifies changes in the chromosome structure or DNA sequence. It is also used to identify changes in genes and proteins, and it also plays a great role in diagnosing genetic disorders and the healthcare industry. In the 1950s, the first genetic prenatal screens were developed as early advancements with the discovery of additional copies of chromosome 21, which caused Down’s syndrome with the development of the karyotyping test, combined with the ability to collect foetal cells from a pregnant woman’s amniotic fluid. Genetic testing can be divided into two eras: Before the Humana Genome Project and after the Human Genome Project. The defining event between them was the announcement of the first draft of the human genome in 2000, a breakthrough in Genetic Testing. In the present scenario, genetic testing techniques such as “whole exome sequencing” and microarrays have increased the accessibility of genetic testing by providing quick and cost-effective data. The wh...

Industry 4.0 has become a common theme throughout the manufacturing fields. It is applied to various manufacturing processes, including quality control and defect detection. Various intelligent systems are being developed for detecting defects with the help of deep learning or AI. Importance of Defect Detection Quality control is a major factor in deciding profits in manufacturing. The defects in manufacturing include not only the visual defects like distortion in shape, wrong placing of components, etc. but it also consists of the performance defects like the malfunctioning of the product, machine, etc. so, there is always a need for reducing defects in the manufactured goods and increase profits. It leads to many innovations that incorporate machine learning and artificial intelligence to defect detection. Why Defect Detection with Artificial Intelligence Makes Sense? One of the most important challenges the manufacturers face is the detection of defects at the surface leve...

Overview: The inclination towards delivering better healthcare services is driven by the need for more precision & effective therapeutics, cost-effective drug development & manufacturing technologies, digitalization, and automation to improve the patient’s quality of life. To reach these milestones, numerous biotechnology, pharmaceuticals, biomedical, diagnostics, and research organizations are adopting various engineering technologies, such as nanotechnology, Augmented and Virtual Reality, Artificial Intelligence, robotics, and 3D printing. However, the major hurdles healthcare providers face are exorbitant R&D activities, meticulous assimilation of new technologies with the existing framework, and constantly changing stringent regulatory standards set by various federal agencies. Know about our expertise in the pharmaceuticals industry@ https://www.iebrain.com/pharmaceuticals/ As the trend is shifting toward day-care treatment, everyone is expecting a rapid and pro...

Although advances have been taking place in the pharmaceutical industry over the past years, the development of new drugs even takes about ~15 years and 800 million to one billion dollars. To cope with this problem, drug repurposing is a newly emerging technique in which existing drugs treat various other diseases. It has been a promising approach because of the opportunity for reduced development timelines and overall costs. It maximizes the potential usage of the existing drugs and increases the number of new drugs. It is a low-cost method of repurposing medications for new medical purposes. In the past few years, various computational approaches have been used in drug repurposing, such as in-silico drug repurposing. Several articles are present in which there is a discussion of how computational methods such as artificial intelligence (AI) and Machine learning (ML) based on network propagation, matrix factorization, and completion are used. So here, Artificial intelligence (AI) an...